The present invention relates to a device for calculating an interaction model.
Currently, the mainstream of computer architectures is the Neumann type. A basic action of the Neumann type architecture is successive execution of an instruction sequence. Heretofore, improvement in performance of the computer has mainly depexided on improvement in clock frequency. However, in recent years, instead of the clock, frequency that has hit the ceiling, a method for improving the performance by parallel processing by realizing multi core in the processor has become a mainstream.
In parallel processing by realisation of multi cores, improvement in the performance is attained by finding portions that can be executed in parallel from a successive instruction sequence (extraction of parallelism), and executing them in parallel. However, it is not easy to extract parallelism from a program that is written down as an instruction sequence from a successive algorithm.
Taking such a situation into consideration, in order to attain improvement in the performance of the computer from now on, it is necessary to shift to essentially parallel information processing not being based on execution of the successive instruction sequence like before. For that purpose, a method for describing a problem suitable to realising essentially parallel information processing is needed instead of a method for describing a problem with the conventional successive instruction sequence.
Various physical phenomena and social phenomena can be represented by the interaction model. The interaction model is a model that is defined with multiple entities constituting the model, an interaction between nodes, and, if necessary, a bias for every node. Various models have been proposed in physics and social science, any one of which can be interpreted as one mode of the interaction model. Moreover, as a feature of the interaction model, it can be enumerated that an influence between the nodes is limited to an interaction between two nodes (interaction between two bodies). For example, considering dynamics of planets in space, although it can foe interpreted as a kind of the interaction model in a respect that an interaction by universal gravitation exists between nodes called planets, an influence between the planets is not only one between two planets bat also three or more planets mutually influence one another, causing complex behaviors (this becomes a so-called three-body problem or many-body problem).
Moreover, in the world of biology, a neural network that models the brain is one example of the interaction model. In the neural network, an artificial neuron that imitates the neuron of the nerve cell is made to serve as a node, and artificial neurons have an interaction called a synaptic connection between them. Moreover, there is also a case where a bias is given to each neuron. In the world of social science, when communication between human beings is considered, for example, it can foe easily understood that there is a node called a human being and an interaction accomplished by a language and communication. Moreover, it can also be imagined that a bias exists individually in each human being. Therefore, a research that imitates human beings' communication as an Ising model etc. that is common in terms of the interaction model and tries to make clear its characteristic are being conducted (for example, see Japanese Unexamined Patent Application Publication No. 2012-217518).
The Ising model that is one example of the interaction models is a model of statistical mechanics for explaining a behavior of a magnetic substance, and is used for research of the magnetic substance. The Ising model is defined as an interaction between sites (spins that take a binary of +1/−1). It is known that finding a ground state of the Ising model whose topology is a nonplanar graph is an NP hard problem. Since the Ising model represents a problem with interaction coefficients that spread in directions of space, it may be able to realise information processing that uses essential parallelism.
Incidentally, since it is the NP hard problem to find the ground state of the Ising model as described above, solving it with the Neumann computer poses a difficulty in the respect of a calculation time. Although an algorithm that attains improvement in speed toy introducing heuristics is also proposed, a calculation that uses a physical phenomenon more directly, not being the Neumann computer, namely, a method for finding the ground state of the Ising model at high speed with an analog computer is proposed.
As such a device, there is a device described in WO 2012/118054, for example. With such a device, parallel degree corresponding to a problem to solve is needed. In the case of the Ising model, corresponding to the number of spins of the Ising model whose ground state should be searched, an element that realizes the spin and the interaction becomes necessary. For example, in a device described in WO 2012/118064, a spin and a laser are made to correspond to each other, the lasers whose number is proportional to the number of the spins become necessary. That is, height of scalability that can realise a large number of elements is required. Therefore, it is desirable that a device for finding the ground state of the Ising model at high speed is one in which a large number of circuits each acting as a unit component are arranged on a semiconductor substrate. That such a design, principle is effective in order to obtain the high scalability may foe clear from examples of semiconductor memory like dynamic random access memory (DRAM) and static random access memory (SRAM) that are currently used widely.
Furthermore, in realizing such a device capable of finding the ground state of the Ising model at high speed, its application must be also considered together with it. Moreover, a cooperative design of the application and the device such as making the device for finding the ground state of the Icing model reflect the application according to its characteristic becomes important.
As applications, one such that a calculation amount is large, and therefore it is hard for the conventional computer to handle it or a huge resource is required is promising. Moreover, since the device as described above can also be expected to be in a smaller size and have a lower power consumption, than the conventional computer, an application to a so-called embedded system that is used being incorporated in various apparatuses can be expected.
As an application having such, a characteristic, there is image processing. Since the image processing has generally many steps of processing each having a large amount of calculation, conventionally there have been many approaches in which an exclusive processor for image processing is developed and used. In particular, image processing whose demand is increasing in recent years is medical-oriented image processing (hereinafter, described as medical image processing). For example, in diagnosis, image segmentation where the inside of the patient's body is photographed by computer tomography (CT) and an affected part such as a tumor is extracted from the image becomes necessary. Moreover, there may come out a necessity of performing the medical image processing in real time such as performing radiation therapy while seeing the inside of the patient body by CT in the future. It has high industrial usefulness that the image processing, typified by the image segmentation, can be realized in real time with a small-sized and small-power-consumption device, and there is an expectation for a device for performing ground state search of the Ising model at high speed as described above.